{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_3000 = pd.read_csv('./train_3000_avg_pred.csv')\n",
    "pred_30465 = pd.read_csv('./train_30465_avg_pred.csv')\n",
    "pred_33465 = pd.read_csv('./train_33465_avg_pred.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #\n",
    "# plt.figure(figsize=(20,10))\n",
    "# plt.subplot(121)\n",
    "# plt.plot(pred_3000.id, pred_3000.score)\n",
    "# plt.title('pred_3000')\n",
    "# plt.subplot(122)\n",
    "# plt.plot(pred_33465.id, pred_33465.score)\n",
    "# plt.title('pred_30465')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc3e8fa38d0>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w1, w2, w3 = 0.2, 0.1, 0.7\n",
    "plt.figure(figsize=(10,8))\n",
    "sns.distplot(pred_3000.score)\n",
    "sns.distplot(pred_30465.score)\n",
    "sns.distplot(pred_33465.score)\n",
    "sns.distplot(w1*pred_3000.score + w2*pred_30465.score + w3*pred_33465.score)\n",
    "plt.legend(['pred_3000','pred_30465','pred_33465','combine'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "com_score = w1*pred_3000.score + w2*pred_30465.score + w3*pred_33465.score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_all = pred_3000[['id']].copy()\n",
    "pred_all['label'] = com_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upper: 0.2930906469  downer: 0.12150934112000003\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "upper = np.percentile(com_score,95)\n",
    "downer = np.percentile(com_score,10)\n",
    "print('upper:',upper,' downer:',downer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_all.loc[(pred_all.label>upper).values,'label']=1\n",
    "pred_all.loc[(pred_all.label<downer).values,'label']=0\n",
    "filter = (pred_all.label>upper)|(pred_all.label<downer)\n",
    "\n",
    "# filter = pred_all.label>upper\n",
    "pred_selec= pred_all.iloc[filter.values]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_selec = pred_selec.astype({'label':np.int64})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3327"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unlabel_y = pred_selec.reset_index(drop=True)\n",
    "sum(unlabel_y.label==1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "unlabel_y.to_csv('unlabel_y.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
